Signal acquisition apparatus and method for distributed compressive sensing and joint signal recovery

Abstract

Disclosed is a multiple sensor system including a plurality of different sensor devices to acquire respective signals sensed from a single signal source, and a signal acquisition apparatus to recover an original signal generated from the signal source. The signal acquisition apparatus recovers the original signal by applying joint recovery, based on characteristics and correlations between the respective sensor devices, to compressive sensing signals independently compressively sensed and transmitted from the respective sensor devices. At this time, a sensing matrix F prearranged with the respective sensor devices and channel information C between the original signal and each sensor device are used for joint recovery.

Description

CROSS-REFERENCE TO RELATED APPLICATION[0001]This application claims the benefit under 35 U.S.A. §119 of Korean Patent Application No. 10-2010-0096128, filed on Oct. 1, 2010 in the Korean Intellectual Property Office, the entirety of which is incorporated herein by reference.BACKGROUND[0002]1. Technical Field[0003]The present disclosure relates to a signal acquisition apparatus and method for distributed compressive sensing and joint signal recovery. More particularly, the present disclosure relates to a signal acquisition apparatus and method for recovering an original signal from compressive sensing signals acquired by a plurality of sensor devices.[0004]The present disclosure was derived from research as a part of big-jump research (or challenge research) support program of the Ministry of Education, Science and Technology [Project management No. NN05850, Project name: coding theoretic compressive sensing for multiple sensor systems].[0005]2. Description of the Related Art[0006]Mu...

AI Technical Summary

Benefits of technology

This approach significantly reduces power consumption and processing time by allowing independent compressive sensing, enabling joint recovery based on sensor characteristics and correlations without inter-sensor communication, and decreases the number of unknowns in signal recovery, thus improving efficiency and practicality for multiple sensor systems.

Problems solved by technology

However, in view of information theory, there is a limit to the total amount of information owned by an arbitrary sensing object.

As such, the multiple sensor system gathers the limited information through various sensors, so that redundant information is likely to occur.

The successive redundancy of information becomes an important factor that shortens the lifespan of a network.

Furthermore, wireless transmission of data having considerable redundancy results in ineffective use of energy accumulated in a battery and causes deterioration in frequency efficiency.

Accordingly, the joint compressive sensing is effective when a distance between sensors is short, but has a problem in that power for transmission / reception is used for signal compression.

This acts as significant overhead in light of total power consumption, thereby causing efficiency deterioration.

Moreover, since the respective sensors of the multiple sensor system are basically realized to provide minimum performance, joint compressive sensing is too complicated to be carried out by such small sensors.

Accordingly, conventional joint compressive sensing is not a practical alternative due to its low effectiveness.

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